---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-2.5b-1000g
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: nucleotide-transformer-2.5b-1000g_ft_Hepg2_1kbpHG19_DHSs_H3K27AC
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# nucleotide-transformer-2.5b-1000g_ft_Hepg2_1kbpHG19_DHSs_H3K27AC

This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-2.5b-1000g](https://huggingface.co/InstaDeepAI/nucleotide-transformer-2.5b-1000g) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4911
- F1 Score: 0.8530
- Precision: 0.9084
- Recall: 0.8041
- Accuracy: 0.8470

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1 Score | Precision | Recall | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.3896        | 1.8657 | 500  | 0.4911          | 0.8530   | 0.9084    | 0.8041 | 0.8470   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.0